The conductivity of the human skull: results of in vivo and in vitro measurements

Oostendorp, Thom F.; Delbeke, Jean; Stegeman, Dick F.

doi:10.1109/tbme.2000.880100

Cited by 416 publications

(311 citation statements)

References 20 publications

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“…A much larger area of synchronized cortex (at least 6-9 cm 2 ) has been reported to be required for interictal spikes to be visible on the scalp (Tao et al, 2007). It is important to note that the skull and other tissues between the brain and the scalp do not attenuate the frequencies up to several KHz any more than the standard EEG frequencies below 40 Hz (Hämäläinen et al, 1993, Oostendorp et al, 2000.…”

Section: Discussionmentioning

confidence: 99%

Automatic detection of fast oscillations (40–200Hz) in scalp EEG recordings

Ellenrieder

Andrade-Valença

Dubeau

et al. 2012

Clinical Neurophysiology

110

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Objective-We aim to automatically detect fast oscillations (40-200 Hz) related to epilepsy on scalp EEG recordings.Methods-The detector first finds localized increments of the signal power in narrow frequency bands. A simple classification based on two features, a narrowband to wideband signal amplitude ratio and an absolute narrowband signal amplitude, then allows for an important reduction in the number of false positives.Results-When compared to an expert, the performance in 15 focal epilepsy patients resulted in 3.6 false positives per minute at 95% sensitivity, with at least 40% of the detected events being true positives. In most of the patients the channels showing the highest number of events according to the expert and the automatic detector were the same.Conclusions-A high sensitivity is achieved with the proposed automatic detector, but results should be reviewed by an expert to remove false positives.Significance-The time required to mark fast oscillations on scalp EEG recordings is drastically reduced with the use of the proposed detector. Thus, the automatic detector is a useful tool in studies aiming to create a better understanding of the fast oscillations visible on the scalp.

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Section: Discussionmentioning

confidence: 99%

Automatic detection of fast oscillations (40–200Hz) in scalp EEG recordings

Ellenrieder

Andrade-Valença

Dubeau

et al. 2012

Clinical Neurophysiology

110

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“…Values commonly used in the literature are in fact the mean values across multiple references (Wagner et al, 2004). These conductivities are mostly measured at 10 Hz or higher frequencies Baumann et al, 1997;Oostendorp et al, 2000;Peters et al, 2001;Hoekema et al, 2003). To date the data for the human head measured in vivo under direct current (0 Hz) are rather scarce and date back over sixty years (Burger and Milaan, 1943;Freygang and Landau, 1955).…”

Section: Electrical Conductivity Values Of Human Tissuesmentioning

confidence: 99%

“…Modern models have compared predictions to human scalp surface recordings (Bangera et al, 2010;Datta et al, 2013), but detailed models have not been validated with intracranial recordings in vivo. Furthermore, the models depend heavily on tissue conductivity values, which have only been measured ex vivo in other animal species Baumann et al, 1997;Oostendorp et al, 2000;Peters et al, 2001;Hoekema et al, 2003). These measures differ from in vivo measurements in humans obtained over half a century ago (Burger and Milaan, 1943;Freygang and Landau, 1955).…”

Section: Introductionmentioning

confidence: 99%

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation

et al. 2017

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Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimated electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.8 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r = 0.86) and depth (r = 0.88) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials.

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“…About 7,000 boundary elements and 3,500 surface nodes were generated from each subject's T 1 -weighted MR images. The relative conductivity values of the brain, skull, and scalp were assumed to be 1, 1/16, and 1, respectively (Haueisen et al, 1997;Oostendorp et al, 2000). The electrode locations were fitted to the boundary elements using anatomical landmarks (nasion and two auricular points) (de Munck et al, 1991) and adjusted manually in the CURRY5 software platform.…”

Section: Eeg Cortical Source Imagingmentioning

confidence: 99%

Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex

Gururajan

Zhang

et al. 2007

Journal of Neuroscience Methods

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The aim of the present study is to investigate the spatial resolution of electroencephalography (EEG) cortical source imaging by localizing the retinotopic organization in the human primary visual cortex (V1). Retinotopic characteristics in V1 obtained from functional magnetic resonance imaging (fMRI) study were used as reference to assess the spatial resolution of EEG since fMRI can discriminate small changes in activation in visual field. It is well-known that the activation of the early C1 component in the visual evoked potential (VEP) elicited by pattern onset stimuli coincides well with the activation in the striate cortex localized by fMRI. In the present experiments, we moved small circular checkerboard stimuli along horizontal meridian and compared the activations localized by EEG cortical source imaging with those from fMRI. Both fMRI and EEG cortical source imaging identified spatially correlated activity within V1 in each subject studied. The mean location error, between the fMRI-determined activation centers in V1 and the EEG source imaging activation peak estimated at equivalent C1 components (peak latency: 74.8 ± 10.6 ms), was 7 mm (25% and 75% percentiles are 6.45 mm and 8.4 mm, respectively), which is less than the change in fMRI activation map by a 3° visual field change (7.8 mm). Moreover, the source estimates at the earliest major VEP component showed statistically good correlation with those obtained by fMRI. The present results suggest that the spatial resolution of the EEG cortical source imaging is can correctly discriminate cortical activation changes in V1 corresponding to less than 3° visual field changes.

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The conductivity of the human skull: results of in vivo and in vitro measurements

Cited by 416 publications

References 20 publications

Automatic detection of fast oscillations (40–200Hz) in scalp EEG recordings

Automatic detection of fast oscillations (40–200Hz) in scalp EEG recordings

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation

Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex

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